Positioning method and device based on PPP-B2b

Abstract

The invention provides a positioning method and device based on PPP-B2b, and belongs to the field of satellite navigation and positioning. The positioning method comprises the steps that firstly, pseudo-range observation data and phase observation data of a BDS satellite and a GPS satellite and PPP-B2b precise correction information are obtained, and the PPP-B2b precise correction information comprises satellite precise orbit parameters, a satellite clock difference reference and initial satellite clock difference deviation between the satellite clock difference reference and each satellite; the method comprises the following steps: setting a receiver clock error parameter in a BDS / GPS observation model based on a satellite clock error reference, taking an initial satellite clock error deviation as a variable added for a pseudo-range observation equation of each satellite in the BDS / GPS observation model, and establishing a precision positioning mathematical model based on PPP-B2b service; and solving the precision positioning mathematical model according to the pseudo-range observation data and the phase observation data of the BDS and the GPS satellites to obtain a precision positioning result of the receiver. According to the method, the precision and reliability of BDS / GPS precision positioning based on PPP-B2b are improved, and the convergence time is saved.

Description

Technical Field

[0001] The invention belongs to the field of satellite navigation and positioning, and in particular relates to a positioning method and equipment based on PPP-B2b. Background Art

[0002] Precise Point Positioning (PPP) is a positioning technology that uses the pseudorange and carrier phase observations observed by a single Global Navigation Satellite System (GNSS) receiver, uses the precise orbit and precise clock products broadcast by the international GNSS service organization, comprehensively considers and corrects various error terms, and obtains three-dimensional coordinates under the International Terrestrial Reference Frame (ITRF). However, since PPP needs to obtain precise data from the international GNSS service (IGS) in real time through the Internet, it cannot achieve real-time high-precision positioning without the Internet. Based on the principle of PPP, the PPP-B2b signal provided by the Beidou-3 system is broadcast by the Group on Earth Observations (GEO) satellite in China and surrounding areas. Corrections such as satellite masks, precise satellite orbits and clock errors, and differential code deviations can provide users with open and free high-precision services. Since the PPP-B2b service is broadcast via satellite, users can achieve high-precision real-time positioning without a network.

[0003] In the prior art, the research on PPP-B2b service mainly focuses on the dual-frequency ionosphere-free combined PPP model. There are few methods for using this service for non-differential non-combined PPP, and various systematic deviations in the PPP-B2b service are not compensated accordingly, so the positioning accuracy is limited. In addition, due to the existence of time reference and initial satellite clock deviation, when performing non-differential non-combined PPP positioning based on PPP-B2b service, there are problems such as slow convergence speed and frequent deterioration of positioning accuracy after convergence. Summary of the invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, the present invention aims to provide a positioning method and device based on PPP-B2b. On the basis of considering the satellite clock error reference and the initial satellite clock error deviation, a receiver clock error parameter is set for the BDS and GPS system respectively, and a systematic deviation parameter is set for each satellite, so as to improve the positioning performance of the non-difference non-combined PPP based on PPP-B2b.

[0005] In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solution:

[0006] In a first aspect, an embodiment of the present invention provides a positioning method based on PPP-B2b, the method comprising the following steps:

[0007] Step S1, acquiring pseudorange observation data and phase observation data of BDS satellites and GPS satellites, as well as PPP-B2b precise correction information; the PPP-B2b precise correction information includes satellite precise orbit parameters, satellite clock error reference, and initial satellite clock error deviation between the satellite clock error reference and each satellite;

[0008] Step S2, establishing a precise positioning mathematical model based on the PPP-B2b service based on the BDS / GPS observation model, specifically comprising: setting receiver clock error parameters in the BDS / GPS observation model based on the satellite clock error reference in the PPP-B2b precise correction information; and using the initial satellite clock error deviation in the PPP-B2b precise correction information as a variable added to the pseudorange observation equation for each satellite in the BDS / GPS observation model;

[0009] Step S3, solving the precise positioning mathematical model based on the PPP-B2b service according to the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, and obtaining the precise positioning result of the receiver.

[0010] As a preferred embodiment of the present invention, the BDS / GPS observation model in which the receiver clock error parameters are set in step S2 is expressed as:

[0011]

[0012] In formula (1), s and r represent a GNSS satellite and a ground receiver respectively, j represents frequency, C represents BDS, G represents GPS, They represent the pseudorange vector and phase vector between satellite s and receiver r at frequency j, respectively; μ represents the unit vector in the line of sight direction, x represents the three-dimensional coordinates of the receiver, Indicates the GPS receiver clock error parameter, ISB C,G Represents the signal channel deviation between BDS and GPS system, is the mapping function of the troposphere between GPS satellite s and receiver r, Z r represents the zenith tropospheric wet delay at the receiver r, μ j represents the ionospheric conversion coefficient at frequency j, and They represent the ionospheric delay parameters between the s satellite and the r receiver in GPS and BDS after absorbing the hardware delay, and represent the phase ambiguity between satellite s and receiver r at frequency j in GPS and BDS respectively.

[0013] As a preferred embodiment of the present invention, in step S2, the mathematical model of precise positioning based on PPP-B2b service is expressed as:

[0014]

[0015] In formula (2), Represents the systematic initial satellite clock bias of GPS system s satellite, Represents the systematic initial satellite clock bias of the BDS system s satellite.

[0016] As a preferred embodiment of the present invention, the steps of solving the mathematical model of precise positioning based on PPP-B2b service in step S3 are as follows:

[0017] Step S31, simplifying the mathematical model of precise positioning based on PPP-B2b service into an observation equation represented by a matrix, as shown in formula (4):

[0018] L=BX+Δ(4)

[0019] In formula (4), L is the observation matrix, B is the design matrix, Δ is the measurement noise matrix, and X is the unknown parameter estimation matrix;

[0020] Step S32, establish the state equation:

[0021] X k+1 =X k +Ω k (6)

[0022] In formula (6), X k+1 , X k are the unknown parameter estimation matrices for the k+1th and kth epochs, respectively, and Ω k is the system noise matrix;

[0023] Step S33, according to the established observation equation and state equation, solve the parameters in the unknown parameter estimation matrix epoch by epoch, and use the three-dimensional coordinates of the receiver as the precise positioning result of the receiver.

[0024] As a preferred embodiment of the present invention, the unknown parameter estimation matrix X is expressed as:

[0025]

[0026] In formula (5), I represents the ionospheric delay of the first frequency of all satellites The matrix is ​​composed of N, which represents all fuzzy parameters The matrix formed.

[0027] As a preferred embodiment of the present invention, each unknown parameter estimation matrix includes receiver three-dimensional coordinates, receiver clock error parameters, initial satellite clock error bias, signal channel bias, zenith tropospheric wet delay, ionospheric delay and phase ambiguity.

[0028] As a preferred embodiment of the present invention, in step S3, the epoch-by-epoch solution adopts the least squares method, the Kalman filter algorithm or the extended Kalman filter algorithm.

[0029] In a second aspect, an embodiment of the present invention further provides a positioning device based on PPP-B2b, the positioning device comprising: an original data acquisition module, a precise positioning mathematical model establishment module and a positioning analysis module; wherein,

[0030] The raw data acquisition module is connected to the precise positioning mathematical model building module and the positioning analysis module at the same time, and is used to obtain the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, as well as the PPP-B2b precise correction information; the precise correction information includes the satellite precise orbit parameters, the satellite clock error reference, and the initial satellite clock error deviation between the satellite clock error reference and each satellite;

[0031] The precise positioning mathematical model building module is connected to the positioning analysis module, and is used to build a precise positioning mathematical model based on the PPP-B2b service based on the BDS / GPS observation model, and is specifically used to: set the receiver clock error parameters in the BDS / GPS observation model based on the satellite clock error reference in the PPP-B2b precise correction information; and use the initial satellite clock error deviation in the PPP-B2b precise correction information as a variable added to the pseudorange observation equation for each satellite in the BDS / GPS observation model;

[0032] The positioning analysis module is used to solve the precise positioning mathematical model based on the PPP-B2b service according to the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, and obtain the precise positioning result of the receiver.

[0033] The technical solution provided by the embodiment of the present invention has the following beneficial effects:

[0034] The PPP-B2b-based positioning method and device provided in the embodiment of the present invention considers the time reference and the initial satellite clock deviation, performs high-frequency precise clock error solution based on Beidou PPP-B2b, first obtains BDS / GPS observation data and PPP-B2b precise correction information in a good environment, sets two clock error parameters in the BDS / GPS observation model based on the PPP-B2b satellite clock error reference, sets a systematic deviation parameter for the pseudorange observation equation of each satellite in the BDS / GPS observation model based on the PPP-B2b initial satellite clock error deviation, and then comprehensively considers the satellite clock error reference and the initial satellite clock error deviation, establishes a precise positioning mathematical model based on the PPP-B2b service and performs precise positioning, thereby effectively improving the accuracy and reliability of BDS / GPS precise positioning based on PPP-B2b, and saving convergence time.

[0035] Of course, it is not necessary to achieve all of the advantages described above at the same time to implement any product or method of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 This is a flow chart of a positioning method based on PPP-B2b according to an embodiment of the present invention;

[0038] Figure 2 is the positioning error time series of PPP-B2b under different clock error types at ULAB station on September 8, 2023;

[0039] Figure 3 This is the time series of positioning errors of PPP-B2b without considering systematic bias and with considering systematic bias at ULAB station on September 8, 2023. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations. It should be noted that the embodiments of the present invention and the features in the embodiments can also be combined with each other without conflict.

[0041] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In the description of the present invention, the terms "first", "second", "third", "fourth", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0042] In view of the positioning problem of PPP-B2b signals, an embodiment of the present invention provides a positioning method and device based on PPP-B2b. Taking into account the time reference and the initial satellite clock error deviation, a high-frequency precise clock error solution is performed based on Beidou PPP-B2b. First, pseudo-range observation data and phase observation data of BDS / GPS in a good environment and PPP-B2b precise correction information are obtained. Receiver clock error parameters are set in the BDS / GPS observation model based on the PPP-B2b satellite clock error reference. A systematic correction variable is set for the pseudo-range observation equation of each satellite in the BDS / GPS observation model based on the PPP-B2b time-invariant initial satellite clock error deviation. A precise positioning mathematical model based on the PPP-B2b service is established by comprehensively considering the satellite clock error reference and the initial satellite clock error deviation. The precise positioning mathematical model is solved according to the pseudo-range observation data and phase observation data of BDS / GPS to obtain receiver precise positioning data, thereby effectively improving the accuracy, reliability and convergence time of BDS / GPS precise positioning based on PPP-B2b.

[0043] Example 1

[0044] like Figure 1 As shown, the positioning method based on PPP-B2b in the embodiment of the present invention includes the following steps:

[0045] Step S1, obtaining pseudorange observation data and phase observation data of BDS satellites and GPS satellites, as well as PPP-B2b precise correction information; the PPP-B2b precise correction information includes satellite precise orbit parameters, satellite clock error reference, and initial satellite clock error deviation between the satellite clock error reference and each satellite.

[0046] In this step, the satellite clock error reference and the initial satellite clock error deviation between each satellite belong to the satellite precise clock error parameters in the PPP-B2b precise correction information. The initial satellite clock error deviation here is the deviation between the satellite clock error reference and each satellite, which belongs to the data in the satellite precise clock error parameters. Although this data is included in the clock error parameters, it is generally ignored, resulting in a decrease in positioning accuracy.

[0047] Step S2, based on the BDS / GPS observation model, establishes a precise positioning mathematical model based on the PPP-B2b service, specifically comprising: setting receiver clock error parameters in the BDS / GPS observation model based on the satellite clock error reference in the PPP-B2b precise correction information; and simultaneously using the initial satellite clock error deviation in the PPP-B2b precise correction information as a variable added to the pseudorange observation equation for each satellite in the BDS / GPS observation model.

[0048] In this step, the receiver clock error parameters are the same for all satellites. The BDS / GPS observation model with the receiver clock error parameters set here is expressed as:

[0049]

[0050] In formula (1), s and r represent a GNSS satellite and a ground receiver respectively, j represents frequency, C represents BDS, G represents GPS, They represent the pseudorange vector and phase vector between satellite s and receiver r at frequency j, respectively; μ represents the unit vector in the line of sight direction, x represents the three-dimensional coordinates of the receiver, Indicates the GPS receiver clock error parameter, ISB C,G Represents the signal channel deviation between BDS and GPS system, is the mapping function of the troposphere between GPS satellite s and receiver r, Z r represents the zenith tropospheric wet delay at the receiver r, μ j represents the ionospheric conversion coefficient at frequency j, and They represent the ionospheric delay parameters between the s satellite and the r receiver in GPS and BDS after absorbing the hardware delay, and represent the floating point ambiguity between satellite s and receiver r at frequency j in GPS and BDS respectively.

[0051] In the BDS / GPS observation model, the initial satellite clock error is set for the pseudo-range observation equation of each satellite, that is, after adding a variable to the pseudo-range observation equation of each satellite, the BDS / GPS observation model is a precise positioning mathematical model based on the PPP-B2b service, which is expressed as:

[0052]

[0053] In formula (2), Represents the systematic initial satellite clock bias of GPS system s satellite, Represents the systematic initial satellite clock bias of the BDS system s satellite.

[0054] It can be seen from formula (2) that the mathematical model of precise positioning based on PPP-B2b service includes clock error parameters based on satellite clock error benchmark, thereby reducing the influence of frequent changes of satellite clock error benchmark on positioning. At the same time, the system deviation parameter based on the initial satellite clock error bias is introduced to mitigate the influence of the initial satellite clock error bias, solve the problems of slow convergence speed of non-difference non-combined PPP positioning based on PPP-B2b service and frequent deterioration of positioning accuracy after convergence, thereby improving the performance of non-difference non-combined PPP positioning based on PPP-B2b, and improving the accuracy, reliability and convergence speed of positioning.

[0055] Step S3, solving the precise positioning mathematical model based on the PPP-B2b service according to the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, and obtaining the precise positioning result of the receiver.

[0056] In this step, the solution process can be completed based on a single measuring station. The steps for solving the mathematical model of precise positioning based on PPP-B2b service are as follows:

[0057] Step S31, simplifying the mathematical model of precise positioning based on PPP-B2b service into an observation equation represented by a matrix, as shown in formula (4):

[0058] L=BX+Δ(4)

[0059] In formula (4), L is the observation matrix, B is the design matrix, Δ is the measurement noise matrix, and X is the unknown parameter estimation matrix:

[0060]

[0061] In formula (5), I represents the ionospheric delay of the first frequency of all satellites The matrix is ​​composed of N, which represents all fuzzy parameters The matrix formed.

[0062] Step S32, establish the state equation:

[0063] X k+1 =X k +Ω k (6)

[0064] In formula (6), X k+1 , X k are the unknown parameter estimation matrices for the k+1th and kth epochs, respectively, and Ω k is the system noise matrix.

[0065] Step S33, according to the established observation equation and state equation, solve the parameters in the unknown parameter estimation matrix such as the receiver three-dimensional coordinates, receiver clock error parameters, initial satellite clock error bias, signal channel bias, zenith tropospheric wet delay, ionospheric delay and phase ambiguity, etc. epoch by epoch, and use the receiver three-dimensional coordinates as the precise positioning result of the receiver.

[0066] In this step, the epoch-by-epoch solution may adopt the least square method, or may adopt the Kalman filter algorithm or the extended Kalman filter algorithm.

[0067] The above method is used to analyze the long-term performance of the mathematical model of non-differenced non-combined PPP-B2b based on a total of 196 days of observation data from six multi-frequency multi-mode GNSS Experimental (MGEX) stations from September 8, 2023 to March 21, 2024. Table 1 shows the RMS positioning accuracy of PPP-B2b in dynamic and static modes at the six stations (from left to right, E / N / U / 3D, in cm).

[0068] Table 1

[0069]

[0070] It can be seen from Table 1 that in the dynamic mode, the three-dimensional positioning accuracy of each station can reach the decimeter level, while in the static mode, the three-dimensional positioning accuracy of each station can reach the centimeter level, indicating that the positioning accuracy of the non-difference non-combined PPP-B2b in the convergence stage can meet the requirements of PPP-B2b positioning.

[0071] Based on the same idea, an embodiment of the present invention further provides a positioning device based on PPP-B2b, and the positioning device includes: an original data acquisition module, a precise positioning mathematical model establishment module and a positioning analysis module.

[0072] The raw data acquisition module is connected to the precise positioning mathematical model building module and the positioning analysis module at the same time, and is used to obtain the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, as well as the PPP-B2b precise correction information; the precise correction information includes the satellite precise orbit parameters, the satellite clock error reference, and the initial satellite clock error deviation between the satellite clock error reference and each satellite;

[0073] The precise positioning mathematical model building module is connected to the positioning analysis module, and is used to build a precise positioning mathematical model based on the PPP-B2b service based on the BDS / GPS observation model, and is specifically used to: set the receiver clock error parameters in the BDS / GPS observation model based on the satellite clock error reference in the PPP-B2b precise correction information; and use the initial satellite clock error deviation in the PPP-B2b precise correction information as a variable added to the pseudorange observation equation for each satellite in the BDS / GPS observation model;

[0074] The positioning analysis module is used to solve the precise positioning mathematical model based on the PPP-B2b service according to the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, and obtain the precise positioning result of the receiver.

[0075] In this embodiment, each module is implemented by a processor, and a memory is appropriately added when storage is required. Among them, the processor can be but is not limited to a microprocessor MPU, a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), other programmable logic devices, discrete gates, transistor logic devices, discrete hardware components, etc. The memory can include a random access memory (RAM) and can also include a non-volatile memory (NVM), such as at least one disk storage. Optionally, the memory can also be at least one storage device located away from the aforementioned processor.

[0076] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center.

[0077] It should also be noted that the PPP-B2b-based positioning device described in this embodiment corresponds to the PPP-B2b-based positioning method, and the description and limitation of the method are also applicable to the system and will not be repeated here.

[0078] Comparative Example 1

[0079] The basic execution steps of this embodiment are substantially the same as those of Embodiment 1, except that a clock error parameter is set for each system in the mathematical model, but a satellite clock error deviation parameter is not set.

[0080] Figure 2 The time series of positioning errors of PPP-B2b under different clock error types at ULAB station on September 8, 2023 are shown. As can be seen from the figure, the positioning results in the mode (Two Clk) with a clock error parameter set for each system are more stable and will not jump. However, the positioning results in the mode (Clk+ISB) with a clock error and an ISB mode set for BDS / GPS will suddenly deteriorate several times after convergence, resulting in unstable and unreliable positioning results.

[0081] Comparative Example 2

[0082] The basic execution steps of this embodiment are substantially the same as those of Embodiment 1, except that a systematic deviation parameter is set for the pseudorange observation equation of each satellite in the mathematical model, but a clock error parameter based on a satellite clock error reference is not set.

[0083] Figure 3 The time series of positioning errors of PPP-B2b without and with systematic bias at ULAB station on September 8, 2023 are shown. As can be seen from the figure, when using the enhanced information of PPP-B2b, considering systematic bias can significantly speed up the convergence speed and reduce the convergence time. The positioning accuracy of the positioning result considering systematic bias after full convergence is equivalent to that without considering it.

[0084] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. It is not intended to limit the scope of the invention claimed for protection, but only represents the preferred embodiment of the present invention. Those skilled in the art should understand that the scope of the invention involved in the present invention is not limited to the technical solution formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the inventive concept. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

Claims

1. A positioning method based on PPP-B2b, characterized in that: The method comprises the following steps: Step S1, acquiring pseudorange observation data and phase observation data of BDS satellites and GPS satellites, as well as PPP-B2b precise correction information; the PPP-B2b precise correction information includes satellite precise orbit parameters, satellite clock error reference, and initial satellite clock error deviation between the satellite clock error reference and each satellite; Step S2, establishing a precise positioning mathematical model based on the PPP-B2b service based on the BDS / GPS observation model, specifically comprising: setting receiver clock error parameters in the BDS / GPS observation model based on the satellite clock error reference in the PPP-B2b precise correction information; and using the initial satellite clock error deviation in the PPP-B2b precise correction information as a variable added to the pseudorange observation equation for each satellite in the BDS / GPS observation model; Step S3, solving the precise positioning mathematical model based on the PPP-B2b service according to the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, and obtaining the precise positioning result of the receiver.

2. The positioning method based on PPP-B2b according to claim 1, characterized in that: The BDS / GPS observation model with the receiver clock error parameters set in step S2 is expressed as: In formula (1), s and r represent a GNSS satellite and a ground receiver respectively, j represents frequency, C represents BDS, G represents GPS, They represent the pseudorange vector and phase vector between satellite s and receiver r at frequency j, respectively; μ represents the unit vector in the line of sight direction, x represents the three-dimensional coordinates of the receiver, Indicates the GPS receiver clock error parameter, ISB C,G Represents the signal channel deviation between BDS and GPS system, is the mapping function of the troposphere between GPS satellite s and receiver r, Z r represents the zenith tropospheric wet delay at the receiver r, μ j represents the ionospheric conversion coefficient at frequency j, and They represent the ionospheric delay parameters between the s satellite and the r receiver in GPS and BDS after absorbing the hardware delay, and represent the phase ambiguity between satellite s and receiver r at frequency j in GPS and BDS respectively.

3. The positioning method based on PPP-B2b according to claim 2, characterized in that: In step S2, the established mathematical model for precise positioning based on PPP-B2b service is expressed as: In formula (2), Represents the systematic initial satellite clock bias of GPS system s satellite, Represents the systematic initial satellite clock bias of the BDS system s satellite.

4. The positioning method based on PPP-B2b according to claim 3, characterized in that: The steps for solving the mathematical model of precise positioning based on PPP-B2b service in step S3 are as follows: Step S31, simplifying the mathematical model of precise positioning based on PPP-B2b service into an observation equation represented by a matrix, as shown in formula (4): L=BX+Δ(4) In formula (4), L is the observation matrix, B is the design matrix, Δ is the measurement noise matrix, and X is the unknown parameter estimation matrix; Step S32, establish the state equation: X k+1 =X k +Oh k (6) In formula (6), X k+1 , X k are the unknown parameter estimation matrices for the k+1th and kth epochs, respectively, and Ω k is the system noise matrix; Step S33, according to the established observation equation and state equation, solve the parameters in the unknown parameter estimation matrix epoch by epoch, and use the three-dimensional coordinates of the receiver as the precise positioning result of the receiver.

5. The PPP-B2b-based positioning method according to claim 4, characterized in that: The unknown parameter estimation matrix X is expressed as: In formula (5), I represents the ionospheric delay of the first frequency of all satellites The matrix is ​​composed of N, which represents all fuzzy parameters The matrix formed.

6. The PPP-B2b-based positioning method according to claim 4, characterized in that: The unknown parameter estimation matrix includes the receiver three-dimensional coordinates, receiver clock error parameters, initial satellite clock error bias, signal channel bias, zenith tropospheric wet delay, ionospheric delay and phase ambiguity.

7. The positioning method based on PPP-B2b according to claim 4, characterized in that: In step S3, the epoch-by-epoch solution adopts the least squares method, the Kalman filter algorithm or the extended Kalman filter algorithm.

8. A positioning device based on PPP-B2b, characterized in that: The positioning device includes: a raw data acquisition module, a precise positioning mathematical model building module and a positioning analysis module; wherein, The raw data acquisition module is connected to the precise positioning mathematical model building module and the positioning analysis module at the same time, and is used to obtain the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, as well as the PPP-B2b precise correction information; the precise correction information includes the satellite precise orbit parameters, the satellite clock error reference, and the initial satellite clock error deviation between the satellite clock error reference and each satellite; The precise positioning mathematical model building module is connected to the positioning analysis module, and is used to build a precise positioning mathematical model based on the PPP-B2b service based on the BDS / GPS observation model, and is specifically used to: set the receiver clock error parameters in the BDS / GPS observation model based on the satellite clock error reference in the PPP-B2b precise correction information; and use the initial satellite clock error deviation in the PPP-B2b precise correction information as a variable added to the pseudorange observation equation for each satellite in the BDS / GPS observation model; The positioning analysis module is used to solve the precise positioning mathematical model based on the PPP-B2b service according to the pseudo-range observation data and phase observation data of the BDS satellite and the GPS satellite, and obtain the precise positioning result of the receiver.

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